Local financial development is crucial for advancing regional financial supply side structural reform, enabling local governments to leverage financial instruments to effectively mobilize land resources and foster competitive growth. The introduction of numerous financial products linked to land-related rights and interests has resulted in a pronounced transmission and interconnection of fiscal and financial risks across regions. This study examines the impact of local financial development on land financialization in China using panel data from prefecture-level cities and detailed information on land mortgages. The findings indicate that the establishment of city commercial banks (CCBs) contributes to the progress of land financialization by incentivizing local government financing vehicles to participate in land mortgage financing, increasing the transfer of debt risks to the financial sector. Notably, the impact of CCBs on land financialization is more pronounced in regions with urban agglomeration, high GDP manipulation, inadequate local financial regulation, and robust implicit government guarantees. Further analysis reveals that CCB establishment has negative spillover effects on land financialization in neighboring areas, while expansion strategies such as establishing intercity branches, engaging in cross-regional mergers, and relaxing regulations have mitigated the rise of land financialization at the regional level. This study provides policy recommendations that focus on reducing local governments’ reliance on land financing and enhancing the prevention and management of financial risks.

We document a positive investment premium in the Chinese market, in contrast to the typical negative investment premium in other markets. The premium only exists when we measure investment by quarterly asset growth, not annual asset growth. A positive premium can be attributed to the fact that quarterly asset growth positively predicts future profitability and GDP growth in the Chinese market, whereas both relationships are negative in the U.S. market. Furthermore, Chinese firms have shorter operating cycles compared to those in the U.S., which explains why quarter data is more valuable.

The study of interconnections between various sectors of the national economy is crucial for understanding the pattern and pace of macroeconomic growth. This paper analyzes the macroeconomic impact of shocks occurring in specific sectors through both supply and demand perspectives and proposes a combination of bottom-up and top-down structural path analysis approaches to trace the transmission path of network spillover effects, where shocks in this paper refer to microeconomic productivity changes and network spillover is defined as the effect on GDP due to the propagation of shocks to other sectors. The research results found that the total spillover effect of primary and secondary industry sectors in China shows an inverted U-shape, and the total spillover effect of tertiary industry sectors shows an upward trend. A large total spillover effect of a sector does not mean that both upward and downward spillover effects are large; for example, the construction industry has high upward spillover effects and low downward spillover effects. The spillover effect of each production layer decreases as the path lengthens, and the distribution is Lshaped.In addition, by identifying the critical paths of spillover effects, we find that the spillover effects of labor-intensive industries, such as wholesale and retail, are decreasing year by year, and the spillover effects of the paths related to the information technology industry are gradually occupying an important position.

This research analyses the ramifications of the COVID-19 pandemic on China's economy, examining the divergent epidemic prevention policies used by local governments. Empirical evidence highlights that the emergence of COVID-19 cases correlates with a 1.13% reduction in quarterly GDP growth. However, when a city's secretary maintains an informal ties with the provincial secretary, GDP growth remains resilient. Analyzing micro-level data, we observe that city secretaries with informal ties tend to enact flexible anti-contagion measures. This flexibility stems from a decreased likelihood of reprimand for virus transmission. Such shields exclusively manifests when incumbent provincial secretaries share informal ties with central leadership. This underscores the interplay of political networks in shaping localized economic responses.

An optimal tax and borrowing plan determines the marginal cost of servicing government debt, p', and makes the government’s debt risk-free. An option to default restricts debt capacity. Optimal debt-GDP ratio dynamics are driven by 1) a primary deficit, 2) interest payments, 3) GDP growth, and 4) hedging costs. Hedging influences debt capacity and debt transition dynamics. For plausible parameter values, we make comparative dynamic quantitative statements about debt-GDP ratio transition dynamics, debt capacity, and how long it would take our example economy to attain that calibrated equilibrium debt capacity.

We document a positive investment premium in the Chinese market, in contrast to the typical negative investment premium in other markets. The premium only exists when we measure investment by quarterly asset growth, not annual asset growth. A positive premium can be attributed to the fact that quarterly asset growth positively predicts future profitability and GDP growth in the Chinese market, whereas both relationships are negative in the U.S. market. Furthermore, Chinese rms have shorter operating cycles compared to those in the U.S., which explains why quarter data is more valuable.

Quantifying the economic loss from climate change in China is crucial for understanding the potential costs and benefits of climate policy within the context of carbon neutrality. This study develops a multidisciplinary and integrated assessment framework for climate damage, which uses the Beijing Climate Center Simple Earth System Model (BCC-SESM) to estimate climatic data under the Representative Concentration Pathways (RCPs) scenarios with the medium Shared Social-economic Pathway (SSP2) scenario in China. This paper estimates climate damage in eight major sectors by a bottom-up approach, makes substantive revisions and calibrations for the sectoral climate damage functions and parameters for China based on the FUND model, and formulates the aggregate climate damage function. Results show that under the Business-as-Usual RCP8.5 scenario, by 2050 human health damage accounts for the largest share (61.92%) of the total climate loss, followed by sea-level rise damage (18.57%) and water resources damage (5.84%). Climate damage in non-market sectors reaches 14.64 trillion CNY, which is a 4.8-fold increase over the climate damage of market sectors which is only 3.02 trillion CNY. The total climate damage function for China is a quadratic function of temperature rise, with climate damage of 5.36%, 5.67%, 5.74%, and 8.16% of the GDP by 2050 under RCP2.6, RCP4.5, RCP6.0, and RCP8.5 respectively, indicating that the marginal climate damage increases non-linearly with temperature rise.

This paper provides new estimates of the housing stock, construction rates and price developments by city tier in China in order to understand where excess supply might be concentrated, and the implications of any significant contraction. We also update estimates of the size of China’s rapidly evolving real estate sector through 2021, allowing one to look at the initial impact of COVID-19, as well as extending the analysis to incorporate urban-expansion related infrastructure construction. We argue that China overall faces imbalances between supply and demand for housing stock, but the problem is significantly deeper in the generally smaller and lower income tier 3 cities, which nevertheless account for more than 60% of both China’s GDP and its housing stock.

目前对金融服务实体经济的分析主要关注总量的配备，本文拟从金融与实体经济间的结构匹配角度切入进行再讨论。本文将我国各省历年的金融结构水平与技术水平分别进行排序并相减，得到各省各年的金融结构与技术水平的匹配度，并对经济增长进行回归。实证结果发现：1）金融结构—技术水平的匹配度与人均 GDP 增长率显著正相关，且该匹配度的解释力要强于金融总量规模、金融结构、技术水平以及金融结构与技术水平的简单交乘项；2）在样本区间内，金融结构略微超过技术水平（3%幅度）时，两者结构匹配效果最好；3）金融规模越高、技术水平越高、金融结构水平越低的地区，结构匹配的效果越强；4）金融结构与技术水平的匹配度可通过促进资本深化和技术进步等渠道对增长发挥正效应。本文的实证发现在内生性处理、转换金融与实体经济的统计口径、改变匹配方式等稳健性处理后仍然保持稳健。这些实证发现将有助于解释中国在证券市场跛足条件下的高速经济增长以及新常态下增长动能转换的方向选择，同时也将为拓宽政府促进金融—实体经济发展的政策组合空间提供经验依据。

本文通过构建包含异质性的家庭消费跨期替代弹性的 DSGE 模型，解释了负向 TFP冲击如何引起实际 GDP 增速下行与房价、债务上涨并存的现象，且负向 TFP 冲击的持续性决定了房价、债务是否出现“逆周期”及其规模。本文基于以下逻辑：负向 TFP 冲击导致收入下滑，消费跨期替代弹性异质性使得部分家庭有倾向于减少住房支出去平滑消费，相对地另一部分家庭倾向于增加住房投资，一方面，随着消费恢复住房需求快速回升，实际住房价格由低到高，同时利率下行，财富从储蓄者向借贷炒房者转移，形成住房财富两极分化，这种分化同时强化了储蓄家庭的居住需求和借贷炒房家庭的投资需求；另一方面，金融中介通过吸收部分家庭的储蓄并向另一类家庭放贷，通过利差不断积累净值，更高的净值对应更多的住房贷款，二者共同推动房价的持续上升。冲击的早期，两类家庭提供更多劳动获得可支配收入，劳动意愿上升部分抵消了产出下滑，随着住房价格上升及信贷繁荣，家庭减少劳动时间，实际产出随之下降，形成房价与债务的“逆周期”现象。央行通过盯住利差，或在货币政策规则中引入金融中介杠杆因子等途径干预信贷能够消除房价与家庭债务的“逆周期”现象。最后，从信贷错配的角度出发，房价上涨是预算软约束下财政刺激、不确定性上升引起的“副作用”。